Add a column with incremental values in Pandas dataFrame

In this article, we will discuss different ways to add a new column in DataFrame with incremental values or numbers.

Table Of Contents

Preparing DataSet

First we will create a DataFrame from list of tuples i.e.

import pandas as pd

# List of Tuples
employees= [('Mark', 'US', 'Tech',   5),
            ('Riti', 'India', 'Tech' ,   7),
            ('Shanky', 'India', 'PMO' ,   2),
            ('Shreya', 'India', 'Design' ,   2),
            ('Aadi', 'US', 'Tech', 11),
            ('Sim', 'US', 'Tech', 4)]

# Create a DataFrame object from list of tuples
df = pd.DataFrame(employees,
                  columns=['Name', 'Location', 'Team', 'Experience'])
print(df)

Output:

     Name Location    Team  Experience
0    Mark       US    Tech           5
1    Riti    India    Tech           7
2  Shanky    India     PMO           2
3  Shreya    India  Design           2
4    Aadi       US    Tech          11
5     Sim       US    Tech           4

Now, suppose we want to add a new column in this DataFrame ‘Age’, and this column should contain incremental values like 31, 32, 33, 34, 35 etc. Let’s see how to do that.

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Add new column with incremental values in Pandas DataFrame

We can call the range() function of Python, to give a range of numbers from start till end. Like, start will be 30 in our case, and end will be 30 + N. Where, N is the number of rows in the DataFrame. So, it will return a sequence of numbers from 31 till 31 + N. Then we can add this squence as a new column in the DataFrame. Let’s see an example,

start = 30

# Add column with incremental values from 30 onwards
df['Age'] = range(start, start + df.shape[0])

print(df)

Output:

     Name Location    Team  Experience  Age
0    Mark       US    Tech           5   30
1    Riti    India    Tech           7   31
2  Shanky    India     PMO           2   32
3  Shreya    India  Design           2   33
4    Aadi       US    Tech          11   34
5     Sim       US    Tech           4   35

Here, we added a new column ‘Age’ in the DataFrame with incremental values.

Add new DataFrame column with incremental values of equal interval

Suppose we want to a add a new column containing incremental values. But the adjacent values should separated by a given step size. We can do that using the range() function. Let’s see the example,

# Add column with incremental values from 30 onwards
# with step size 5
df['Age'] = range(start, start + (5 * df.shape[0]), 5)

print(df)

Output:

     Name Location    Team  Experience  Age
0    Mark       US    Tech           5   30
1    Riti    India    Tech           7   35
2  Shanky    India     PMO           2   40
3  Shreya    India  Design           2   45
4    Aadi       US    Tech          11   50
5     Sim       US    Tech           4   55

Here, we added a new column ‘Age’ in the DataFrame with incremental values, but each value in this column is greater than previous value by 5.

Summary

Today, we saw how to add a new column in DataFrame with incremental values. Thanks.

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Thanks for reading.

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